Young-Ae Kwon
Papers
1
Total Citations
3
H-Index
1
About
Young-Ae Kwon’s research centers on autonomous mobile robotics, with a particular focus on navigation and exploration in unknown environments. Her most-cited work, “Internal and external frontier‐based algorithm for autonomous mobile robot exploration in unknown environment” (2021), tackles a fundamental challenge in robotics: how a robot can efficiently traverse and map an area without prior environmental knowledge. Kwon’s algorithm introduces a dual frontier-based approach, optimizing exploration by balancing internal and external boundaries to reduce redundant movement and improve coverage. This contribution is critical for applications in search-and-rescue, planetary exploration, and industrial automation. With 3 citations, her paper is a targeted contribution to the field, offering a practical solution to a persistent problem in autonomous navigation. Kwon’s work demonstrates a keen ability to address real-world constraints, making her a promising voice in robotics research. Her algorithm provides a clear, implementable framework for future studies, and her focus on efficiency and adaptability positions her as a researcher to watch in the evolving landscape of autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1